The instrument development and design of a prototype frequency-domain optical imaging device for breast cancer detection is described in detail. This device employs radio-frequency intensity modulated near-infrared light to image quantitatively both the scattering and absorption coefficients of tissue. The functioning components of the system include a laser diode and a photomultiplier tube, which are multiplexed automatically through 32 large core fiber optic bundles using high precision linear translation stages. Image reconstruction is based on a finite element solution of the diffusion equation. This tool for solving the forward problem of photon migration is coupled to an iterative optical property estimation algorithm, which uses a Levenberg-Marquardt routine with total variation minimization. The result of this development is an automated frequency-domain optical imager for computed tomography which produces quantitatively accurate images of the test phantoms used to date. This paper is a description and characterization of an automated frequency-domain computed tomography scanner, which is more quantitative than earlier systems used in diaphanography because of the combination of intensity modulated signal detection and iterative image reconstruction.
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http://dx.doi.org/10.1364/oe.1.000391 | DOI Listing |
BMC Cancer
January 2025
Young Academy of Gynecologic Oncology (JAGO), Nord-Ostdeutsche Gesellschaft für Gynäkologische Onkologie (NOGGO), Berlin, Germany.
Background: The integration of immune checkpoint inhibitors (ICIs) into routine gynecologic cancer treatment requires a thorough understanding of how to manage immune-related adverse events (irAEs) to ensure patient safety. However, reports on real-world clinical experience in the management of ICIs in gynecologic oncology are very limited. The aim of this survey was to provide a real-world overview of the experiences and the current state of irAE management of ICIs in Germany, Switzerland, and Austria.
View Article and Find Full Text PDFBMC Cancer
January 2025
Division de la Recherche Clinique, Centre Jean PERRIN, 58 rue Montalembert, Clermont-Ferrand, 63011, France.
Background: Over the past twenty years, the post-cancer rehabilitation has been developed, usually in a hospital setting. Although this allows better care organization and improved security, it is perceived as stressful and restrictive by the "cancer survivor". Therefore, the transfer of benefits to everyday life is more difficult, or even uncertain.
View Article and Find Full Text PDFBreast Cancer
January 2025
Tepe Prime, MKA Breast Cancer Clinic, 06800, Ankara, Turkey.
Breast Cancer Res Treat
January 2025
Google Health, 1600 Amphitheatre Pkwy, Mountain View, CA, 94043, USA.
Purpose: Many breast centers are unable to provide immediate results at the time of screening mammography which results in delayed patient care. Implementing artificial intelligence (AI) could identify patients who may have breast cancer and accelerate the time to diagnostic imaging and biopsy diagnosis.
Methods: In this prospective randomized, unblinded, controlled implementation study we enrolled 1000 screening participants between March 2021 and May 2022.
Mol Biol Rep
January 2025
Department of Clinical Pathology, Faculty of Medicine, Alexandria University, Alexandria, Egypt.
Background: The identification of circulating potential biomarkers may help earlier diagnosis of breast cancer, which is critical for effective treatment and better disease outcomes. We aimed to study the role of circ-FAF1 as a diagnostic biomarker in female breast cancer using peripheral blood samples of these patients, and to investigate the relation between circ-FAF1 and different clinicopathological features of the included patients.
Methods And Results: This case-control study enrolled 60 female breast cancer patients and 60 age-matched healthy control subjects.
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